Ultra-processed foods (UPF), defined using frameworks such as NOVA, are increasingly linked to adverse health outcomes, driving interest in ways to identify and monitor their consumption. Artificial intelligence (AI) offers potential, yet its application in classifying UPF remains underexamined. To address this gap, we conducted a scoping review mapping how AI has been used, focusing on techniques, input data, classification frameworks, accuracy and application. Studies were eligible if peer-reviewed, published in English (2015–2025), and they applied AI approaches to assess or classify UPF using recognised or study-specific frameworks. A systematic search in May 2025 across PubMed, Scopus, Medline and CINAHL identified 954 unique records with eight ultimately meeting the inclusion criteria; one additional study was added in October following an updated search after peer review. Records were independently screened and extracted by two reviewers. Extracted data covered AI methods, input types, frameworks, outputs, validation and context. Studies used diverse techniques, including random forest classifiers, large language models and rule-based systems, applied across various contexts. Four studies explored practical settings: two assessed consumption or purchasing behaviours, and two developed substitution tools for healthier options. All relied on NOVA or modified versions to categorise processing. Several studies reported predictive accuracy, with F1 scores from 0·86 to 0·98, while another showed alignment between clusters and NOVA categories. Findings highlight the potential of AI tools to improve dietary monitoring and the need for further development of real-time methods and validation to support public health.

The development of the forcing method has shown that several key questions regarding infinite sets cannot be settled under ZFC alone. The most widely supported view is that this undecidability simply reflects the limitations of ZFC in addressing all mathematical problems. This perspective has motivated an extensive search for new axioms—the so-called large cardinal axioms—which, when added to ZFC, yield a deeper and more robust understanding of the set-theoretic universe. Along this line, the dissertation is divided into three thematic blocks, each of them framed within these extensions of ZFC:

• • Very large cardinals at the threshold of Kunen inconsistency, with a focus on elementarity and cardinal correctness (Chapter 2).

• • Generalized Descriptive Set Theory at singular strong limit cardinals of countable cofinality, with a focus on two regularity properties (Chapter 3).

• • Covering lemmas and Woodin’s HOD Dichotomy through the lens of Shelah’s pcf theory (Chapter 4).

Specifically, Chapter 2 establishes an inconsistency result using tools from singular cardinal combinatorics and Shelah’s pcf theory, proving the nonexistence of cardinal preserving elementary embeddings into V and establishing thereby a limitation in the hierarchy of large cardinal axioms. The proof is based on the notion of good scales and its connection with Jónsson cardinals. Chapter 3 proves a consistency result obtained via a Prikry-type forcing construction, providing a singular-cardinal analogue of Solovay’s theorem. This thematic block is inspired by Woodin’s Axiom $I_0$ which provides the appropriate axiomatic framework to develop Generalized Descriptive Set Theory in generalized Baire/Cantor spaces at singular cardinals. Concretely, we construct a model of ZFC where $\kappa $ is a strong limit singular cardinal with countable cofinality, and every subset of ${}^\omega \kappa $ in $L(V_{\kappa +1})$ has both the $\kappa $-Perfect Set Property and the $\vec {\mathcal {U}}$-Baire Property. Chapter 4 further explores the study of “covering lemmas” and Woodin’s HOD Dichotomy, employing both the perspective and the tools of pcf theory. Specifically, the connection between the cover property and a new pcf-theoretic concept—called the scale property—is analyzed. This analysis builds a bridge between combinatorial principles in pcf theory and the structural behavior of HOD.

Abstract prepared by Sebastiano Thei.

E-mail: thei91.seba@gmail.com.

URL: https://air.uniud.it/handle/11390/1316344?mode=full.

We combine Indigenous and Western scientific ontologies to explore the deep history of pinyon pine in the Holocene Great Basin. We address 61 Theft of Pine Nuts (TPN) oral histories transcribed over the last 152 years. Contemporary Paiute, Shoshone, and Wá∙šiw storytellers still tell these narratives, which five Indigenous coauthors heard growing up. Considered judiciously and in concert with independent corroboration, these traditional oral histories (often dismissed as “myths”) potentially convey significant historical landmarks. Four themes emerge: (1) pine nuts have been a driving force in Indigenous Great Basin lifeways for millennia, (2) TPN oral histories pinpoint homelands beyond which pinyon trees grow today, (3) TPN narratives encode shifting animal biodiversity, and (4) massive ice barriers (likely dating to the Late Pleistocene) thwarted pine-nut thieves. We seek out elements encoded in oral histories that reflect pinyon-pine ecology and pinyon as a long-term vehicle of survivance among Indigenous Great Basin communities. Our findings reflect Roger Echo-Hawk’s (2000:90) wise counsel that “written words and spoken words need not compete for authority in academia, nor should the archaeological record be viewed as the antithesis of oral records. Peaceful coexistence and mutual interdependence offer more useful paradigms for these ‘ways of knowing.’”

The “innovation championship” model has been instrumental in explaining policy innovations in China’s local governments, particularly at the provincial level. However, discrepancies between this model and real-world cases raise questions about its broader applicability. To address this, we employ a dichotomous framework (innovation generation/borrowing) and conduct multi-level quantitative analyses of government work reports. Our analysis suggests that between 2003 and 2022, most provincial innovations were driven by the championship model, which relies on central government recognition, while others were shaped by peer recognition mechanisms. Together, these form a “central and peer” (CP) model that prioritizes innovation generation while incorporating a degree of innovation borrowing. This CP model differentiates the innovation functions among provincial governments, which have formed a collective innovation network: pioneering provinces generate model policies, while others capitalize on these opportunities. Moreover, the extent of the central authority’s influence determines the relative importance of these two mechanisms.

This study examined the metacercariae of trematodes in cnidarian jellyfish around Japan to demonstrate the importance of the jellyfish as the second intermediate or paratenic hosts. Trematodes were sampled from cnidarian jellyfish in seven coastal regions of Japan between 2024 and 2025. Trematodes (adults and metacercariae) were also obtained from marine fish and arrow worms and included for data comparisons. DNA barcoding was used for the species identification of metacercariae in the jellyfish and for elucidating their partial life cycles. Eight cnidarian species (245 individuals) were sampled, with metacercarial infection detected in seven host species. Based on morphological and molecular analyses, the metacercariae were classified into nine species belonging to three families, Accacoeliidae, Hemiuridae, and Lepocreadiidae. Six of these species were identified as the same species of adults isolated from fish hosts around Japan, although species names of two of the six remained unclear. The remaining three trematode species were assumed to belong to Lepocreadiidae, a major group of fish trematodes. These findings indicate that cnidarian jellyfish are important intermediate or paratenic hosts of fish trematodes in Japanese waters, as has been reported in other areas in previous studies. Moreover, a metacercaria occasionally detected in an arrow worm was identified as the same species as those in jellyfish, suggesting predator–prey relationships between these hosts. The study also synonymised Tetrochetus hamadai Fukui and Ogata, 1935, T. aluterae (Hanson, 1955), and T. mitenevi Zubchenko, 1978, with T. coryphaenae Yamaguti, 1934, based on molecular and morphological data.

Cylicospirura is a genus of spirocercid nematodes infecting felids around the globe. Eleven species have been characterised, with C. felineus and C. subaequalis being reported in jaguarundis, Herpailurus yagouaroundi, from Brazil. Herein, we described spirocercid reddish worms collected from three jaguarundis from Costa Rica by using hierarchical clustering and dendrogram plots of morphological characters reported from our specimens and compared to other Cylicospirura spp., histopathological observations of associated lesions, and phylogenetic analyses of both mitochondrial and ribosomal loci. Nematodes were found within stomach nodules located in the submucosa causing a pyogranulomatous, multifocal, nodular, and sclerosing gastritis. In addition, the collected worms differed from their congeners by having a longer body and smaller muscular and glandular oesophagus, subsequently showing lower total oesophagus to body length percentage and ratio of glandular to muscular oesophagus. Cytochrome oxidase subunit 1 and internal transcribed spacer 1 analyses revealed that worms were 8.33 to 8.66% different from C. felineus, C. subaequalis, or C. petrowi and 15.2 to 15.4% different from C. petrowi, respectively. Moreover, sequences derived from collected worms clustered separately from other Cylicospirura spp. available in GenBank® in the phylogenetic trees. By using an integrative taxonomy approach, the nematodes collected from stomach nodules of jaguarundis were described as a new taxon, for which the name Cylicospirura wishkai sp. nov. is proposed.

The lower limb exoskeleton is a typical wearable robot designed to assist human motion. However, its system stability and performance are often compromised due to unknown model parameters and inadequate control strategies. Therefore, it is crucial to explore the parametric identification of the exoskeleton and the design of corresponding control strategies for human-exoskeleton cooperative motion. First, an exoskeleton platform is developed to provide experimental validation. Simultaneously, a two-degree-of-freedom (2-DOF) exoskeleton model is constructed using the Lagrange method. The neighborhood field optimization (NFO) technique is then applied to identify the unknown model parameters of the exoskeleton. Additionally, the excitation trajectories for the exoskeleton are developed by the NFO method, incorporating several motion constraints to enhance the accuracy of model identification. An admittance controller is implemented to enable active control of the exoskeleton, allowing it to align with human intention and thereby improving the wearability and comfort of the device. Finally, both simulation and experimental results are compared and verified on the platform. These results demonstrate that the NFO method achieves superior identification accuracy compared to particle swarm optimization (PSO) and genetic algorithm (GA).

Individuals with severe mental illness face a significantly reduced life expectancy compared to the general population. Addressing key modifiable risk factors is essential to reduce these alarming rates of mortality in this population. Nutritional psychiatry has emerged as an important field of research, highlighting the important role of nutrition on mental health outcomes. However, individuals with severe mental illness often encounter barriers to healthy eating, including poor diet quality, medication-related side effects such as increased appetite and weight gain, food insecurity and limited autonomy over food choices. While nutrition interventions play a key role in improving health outcomes and should be a standard part of care, their implementation remains challenging. Digital technology presents a promising alternative support model, with the potential to address many of the structural and attitudinal barriers experienced by this population. Nonetheless, issues such as digital exclusion and low digital literacy persist. Integrating public and patient involvement, along with behavioural science frameworks, into the design and delivery of digital nutrition interventions can improve their relevance, acceptability and impact. This review discusses the current and potential role of digital nutrition interventions for individuals with severe mental illness, examining insights, challenges and future directions to inform research and practice.

Despite the recent methodological advancements in causal panel data analysis, concerns remain about unobserved unit-specific time-varying confounders that cannot be addressed by unit or time fixed effects or their interactions. We develop a Bayesian sensitivity analysis (BSA) method to address the concern. Our proposed method is built upon a general framework combining Rubin’s Bayesian framework for model-based causal inference (Rubin [1978], The Annals of Statistics 6(1), 34–58) with parametric BSA (McCandless, Gustafson, and Levy [2007], Statistics in Medicine 26(11), 2331–2347). We assess the sensitivity of the causal effect estimate from a linear factor model to the possible existence of unobserved unit-specific time-varying confounding, using the coefficients of the treatment variable and observed confounders in the model for the unobserved confounding as sensitivity parameters. We utilize priors on these coefficients to constrain the hypothetical severity of unobserved confounding. Our proposed approach allows researchers to benchmark the assumed strength of confounding on observed confounders more systematically than conventional frequentist sensitivity analysis techniques. Moreover, to cope with convergence issues typically encountered in nonidentified Bayesian models, we develop an efficient Markov chain Monte Carlo algorithm exploiting transparent parameterization (Gustafson [2005], Statistical Science 20(2), 111–140). We illustrate our proposed method in a Monte Carlo simulation study as well as an empirical example on the effect of war on inheritance tax rates.

This study offers a phenomenological exploration of unchosen pregnancy as a distinct temporal experience. By bracketing the traditionally dominant concept of pregnancy as culminating in birth, this study unveils the unique temporal contours of early pregnancy, particularly when it is not chosen. Through a critical phenomenology analysis, this study demonstrates how unchosen pregnancy is characterized by extreme temporal disorientation, a heightened experience of multiple temporal layers, and a profound loss of temporal grounding. This description of unchosen pregnancy is intended to open new pathways of thought on the ethical issue of abortions and expand the phenomenological understanding of pregnancy.

Sarcopenia, the age-related decline in muscle mass and strength, is a contributor to frailty and reduced quality of life. Emerging evidence suggests an emerging role of the gut microbiome in modulating skeletal muscle through microbial species and metabolites, such as short-chain fatty acids (SCFAs), potentially influencing inflammation, nutrient absorption, and glucose and protein metabolism. This review considers the potential of probiotics, prebiotics, and synbiotics as interventions to mitigate sarcopenia based on animal and human studies, while providing a critique of present barriers that need to be addressed. Preclinical models, including germ-free mice and faecal microbiota transplantation, demonstrate that gut microbiota from healthy or young donors may enhance overall muscle health via reductions in inflammatory and muscle atrophy markers. Limited human studies show that probiotics such as Lactobacillus and Bifidobacterium could improve branched-chain amino acid (BCAA) bioavailability and potentially sarcopenia indices, although findings have been inconsistent. Particularly, challenges including inconsistent microbial assessments, lack of dietary control and interindividual variability due to diet, age, genetics, comorbidities and medications may hinder progress in this field. Delivery methods (e.g. capsules, fermented foods or fortified products) could further complicate efficacy through probiotic stability and dietary restrictions in older adults. Standardised protocols [e.g. Strengthening The Organisation and Reporting of Microbiome Studies (STORMS) checklist] and multi-omics approaches may be critical to address these limitations and identify microbial signatures linked to sarcopenia outcomes. While preclinical evidence highlights mechanistic pathways pertinent to amino acid metabolism, translating findings to humans requires rigorous experimental trials.